_base_ = ["../2021half/face_license.py", "../_base_/default_runtime.py"]
model = dict(
    type="GFL",
    # pretrained='/workspace/cm-mmlab/model-zoo/mmcls/repvgg_s-f9b3ea19.pth',
    backbone=dict(
        type="RepVGG",
        num_blocks=[2, 4, 14, 1],
        width_multiplier=[1, 0.5, 0.5, 1],
        deploy=False,
    ),
    neck=dict(
        type="FPN",
        in_channels=[64, 64, 128, 512],
        out_channels=64,
        start_level=1,
        add_extra_convs="on_output",
        num_outs=3,
    ),
    bbox_head=dict(
        type="GFLHeadSepConvDS",
        num_classes=2,
        num_ins=3,
        in_channels=64,
        stacked_convs=3,
        feat_channels=64,
        anchor_generator=dict(
            type="AnchorGenerator",
            ratios=[1.0],
            octave_base_scale=2,
            scales_per_octave=1,
            strides=[8, 16, 32],
        ),
        loss_cls=dict(
            type="QualityFocalLoss", use_sigmoid=True, beta=2.0, loss_weight=1.0
        ),
        loss_dfl=dict(type="DistributionFocalLoss", loss_weight=0.25),
        reg_max=15,
        loss_bbox=dict(type="GIoULoss", loss_weight=2.0),
    ),
)
# training and testing settings
train_cfg = dict(
    assigner=dict(type="ATSSAssigner", topk=9),
    allowed_border=-1,
    pos_weight=-1,
    debug=False,
)
test_cfg = dict(
    nms_pre=1000,
    min_bbox_size=0,
    score_thr=0.05,
    nms=dict(type="nms", iou_thr=0.6),
    max_per_img=100,
)


seed = 166
find_unused_parameters = True
